mlsanityData to 14 Oct 2026

Instruct-FinGPT: Financial Sentiment Analysis by Instruction Tuning of General-Purpose Large Language Models

arXiv 2306.12659 ↗First posted 22 Jun 2023cs.CL cs.LG q-fin.STcited by 58

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Abstract (arXiv)

Sentiment analysis is a vital tool for uncovering insights from financial articles, news, and social media, shaping our understanding of market movements. Despite the impressive capabilities of large language models (LLMs) in financial natural language processing (NLP), they still struggle with accurately interpreting numerical values and grasping financial context, limiting their effectiveness in predicting financial sentiment. In this paper, we introduce a simple yet effective instruction tuning approach to address these issues. By transforming a small portion of supervised financial sentiment analysis data into instruction data and fine-tuning a general-purpose LLM with this method, we achieve remarkable advancements in financial sentiment analysis. In the experiment, our approach outperforms state-of-the-art supervised sentiment analysis models, as well as widely used LLMs like ChatGPT and LLaMAs, particularly in scenarios where numerical understanding and contextual comprehension are vital.

Key facts. Cited by 58 papers in the map (data through 14 Oct 2026). Builds on 9 of its 28 references that are in the map. First posted on arXiv 22 Jun 2023.

Builds on

9 of 28 references.

References · 9

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  3. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,780
  4. 2017Decoupled Weight Decay Regularizationcited by 1,831
  5. 2023BloombergGPT: A Large Language Model for Financecited by 939
  6. 2019FinBERT: Financial Sentiment Analysis with Pre-trained Language Modelscited by 385
  7. 2013Good Debt or Bad Debt: Detecting Semantic Orientations in Economic Textscited by 310
  8. 2022WHEN FLUE MEETS FLANG: Benchmarks and Large Pre-trained Language Model for Financial Domaincited by 117
  9. 2016Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corporacited by 19

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 9; 2024: 20; 2025: 25; 2026: 4.

58 papers.

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  1. 2023Large Language Models in Finance: A Surveycited by 226
  2. 2024TradingAgents: Multi-Agents LLM Financial Trading Frameworkcited by 188
  3. 2024OpenFedLLM: Training Large Language Models on Decentralized Private Data via Federated Learningcited by 128
  4. 2023Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlookcited by 110
  5. 2024A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challengescited by 90
  6. 2023FinGPT: Instruction Tuning Benchmark for Open-Source Large Language Models in Financial Datasetscited by 69
  7. 2023Enhancing Financial Sentiment Analysis via Retrieval Augmented Large Language Modelscited by 68
  8. 2023FinGPT: Democratizing Internet-scale Data for Financial Large Language Modelscited by 67
  9. 2024Empowering Time Series Analysis with Large Language Models: A Surveycited by 60
  10. 2025Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Surveycited by 51
  11. 2024Financial Report Chunking for Effective Retrieval Augmented Generationcited by 46
  12. 2023Deficiency of Large Language Models in Finance: An Empirical Examination of Hallucinationcited by 41
38 more
  1. 2024FinRobot: An Open-Source AI Agent Platform for Financial Applications using Large Language Modelscited by 40
  2. 2024TelecomGPT: A Framework to Build Telecom-Specfic Large Language Modelscited by 40
  3. 2024MarS: a Financial Market Simulation Engine Powered by Generative Foundation Modelcited by 28
  4. 2023GrammarGPT: Exploring Open-Source LLMs for Native Chinese Grammatical Error Correction with Supervised Fine-Tuningcited by 23
  5. 2024FinLlama: Financial Sentiment Classification for Algorithmic Trading Applicationscited by 23
  6. 2024Large Language Models are Zero-Shot Next Location Predictorscited by 22
  7. 2023An Interdisciplinary Outlook on Large Language Models for Scientific Researchcited by 15
  8. 2025Trading-R1: Financial Trading with LLM Reasoning via Reinforcement Learningcited by 15
  9. 2024Tri-Level Navigator: LLM-Empowered Tri-Level Learning for Time Series OOD Generalizationcited by 12
  10. 2025Deep Learning for Time Series Forecasting: A Surveycited by 10
  11. 2024GreedLlama: Performance of Financial Value-Aligned Large Language Models in Moral Reasoningcited by 9
  12. 2025Large Language Models for Subjective Language Understanding: A Surveycited by 9
  13. 2026Agentic Trading: When LLM Agents Meet Financial Marketscited by 7
  14. 2024A Scoping Review of ChatGPT Research in Accounting and Financecited by 6
  15. 2025Are Large Language Models Good In-context Learners for Financial Sentiment Analysis?cited by 5
  16. 2025Interpretable LLMs for Credit Risk: A Systematic Review and Taxonomycited by 5
  17. 2024Examining Independence in Ensemble Sentiment Analysis: A Study on the Limits of Large Language Models Using the Condorcet Jury Theoremcited by 4
  18. 2025Will LLMs be Professional at Fund Investment? DeepFund: A Live Arena Perspectivecited by 4
  19. 2025Bridging Language Models and Financial Analysiscited by 4
  20. 2025FinDPO: Financial Sentiment Analysis for Algorithmic Trading through Preference Optimization of LLMscited by 4
  21. 2025Metadata-Driven Retrieval-Augmented Generation for Financial Question Answeringcited by 4
  22. 2024Construction of Domain-specified Japanese Large Language Model for Finance through Continual Pre-trainingcited by 3
  23. 2024The Construction of Instruction-tuned LLMs for Finance without Instruction Data Using Continual Pretraining and Model Mergingcited by 3
  24. 2025FinSphere, a Real-Time Stock Analysis Agent Powered by Instruction-Tuned LLMs and Domain Toolscited by 2
  25. 2025TAP: Two-Stage Adaptive Personalization of Multi-Task and Multi-Modal Foundation Models in Federated Learningcited by 2
  26. 2025The Effectiveness of Approximate Regularized Replay for Efficient Supervised Fine-Tuning of Large Language Modelscited by 2
  27. 2026Multi-Stage Evolutionary Model Merging with Meta Data Driven Curriculum Learning for Sentiment-Specialized Large Language Modelingcited by 2
  28. 2023PatternGPT :A Pattern-Driven Framework for Large Language Model Text Generationcited by 1
  29. 2024Financial Sentiment Analysis: Leveraging Actual and Synthetic Data for Supervised Fine-tuningcited by 1
  30. 2025Multimodal Stock Price Prediction: A Case Study of the Russian Securities Marketcited by 1
  31. 2025Enhancing Cryptocurrency Sentiment Analysis with Multimodal Featurescited by 1
  32. 2025Evaluating Large Language Models for Stance Detection on Financial Targets from SEC Filing Reports and Earnings Call Transcriptscited by 1
  33. 2025BondBERT: What we learn when assigning sentiment in the bond marketcited by 1
  34. 2025Fine-tuning of lightweight large language models for sentiment classification on heterogeneous financial textual datacited by 1
  35. 2024Kuaiji: the First Chinese Accounting Large Language Modelcited by 0
  36. 2024Energy Efficient Protein Language Models: Leveraging Small Language Models with LoRA for Controllable Protein Generationcited by 0
  37. 2024Enhancing Financial Domain Adaptation of Language Models via Model Augmentationcited by 0
  38. 2025DBOT: Artificial Intelligence for Systematic Long-Term Investingcited by 0

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